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WSGI (Web Server Gateway Interface) is a standard interface between web servers and Python web applications or frameworks. To define a WSGI handler in a Python file, you need to create a Python function that follows the WSGI specification. This function should accept two parameters, the environment (environ) and a start_response callable.

Here's a simple example of a WSGI handler:

def wsgi_handler(environ, start_response):
    status = '200 OK'
    headers = [('Content-type', 'text/plain')]
    start_response(status, headers)

    response_body = 'Hello, WSGI!'
    return [response_body.encode('utf-8')]

In this example, wsgi_handler is a WSGI-compliant function that accepts the environment and start_response parameters, sets the status and headers, and returns a list containing a single byte string.

How to Return JSON from WSGI handler ?

To return JSON from a WSGI handler, you'll need to modify the response content type and convert the response body into a JSON formatted string. You can use the json module from Python's standard library to achieve this. Here's an example:

import json

def wsgi_handler(environ, start_response):
    status = '200 OK'
    headers = [('Content-type', 'application/json')]
    start_response(status, headers)

    response_data = {
        'message': 'Hello, WSGI!',
        'data': {
            'key': 'value',
        }
    }
    response_body = json.dumps(response_data)
    return [response_body.encode('utf-8')]

In this example, the Content-type header is set to 'application/json' to indicate that the response is a JSON object. The response_data dictionary is then converted to a JSON-formatted string using json.dumps() and returned as a byte string.

Google stores emails on their servers in a distributed system that is designed to provide high availability, scalability, and reliability. Here are some key aspects of how Google stores emails:

1. Distributed storage: Google uses a distributed file system called Colossus to store emails. Colossus is designed to handle petabytes of data and provides high availability, scalability, and fault tolerance.

2. Redundancy: Google stores multiple copies of each email in different data centers to ensure that emails are not lost due to hardware failures or disasters.

Scalability: SQL Server is designed to support large-scale data processing, making it ideal for handling massive datasets and high-traffic applications.

Integration: SQL Server can be easily integrated with other Microsoft tools and technologies, such as Azure and Power BI, providing a seamless data management and analysis experience.

Performance: SQL Server is optimized for fast data processing, query performance, and indexing, delivering superior speed and reliability compared to many competitors.

A step-by-step guide to check the MD5 checksum of a file in Linux, with examples: